Geneva, Switzerland: Mathematical prediction models are better than doctors at predicting the outcomes and responses of lung cancer patients to treatment, according to new research presented today (Saturday) at the 2nd Forum of the European Society for Radiotherapy and Oncology (ESTRO).
These differences apply even after the doctor has seen the patient, which can provide extra information, and knows what the treatment plan and radiation dose will be.
Machine learning models already ought to be extensively employed for diagnosis and generation of treatment plans. The human mind can't handle the amount of information available. Plus, the mind is easily biased and the subconscious throws up lots of wrong ideas.
Diagnostic signals and treatment options are proliferating.
"The number of treatment options available for lung cancer patients are increasing, as well as the amount of information available to the individual patient. It is evident that this will complicate the task of the doctor in the future," said the presenter, Dr Cary Oberije, a postdoctoral researcher at the MAASTRO Clinic, Maastricht University Medical Center, Maastricht, The Netherlands. "If models based on patient, tumour and treatment characteristics already out-perform the doctors, then it is unethical to make treatment decisions based solely on the doctors' opinions. We believe models should be implemented in clinical practice to guide decisions."
Too much information for oncologists to handle.
President of ESTRO, Professor Vincenzo Valentini, a radiation oncologist at the Policlinico Universitario A. Gemelli, Rome, Italy, commented: "The booming growth of biological, imaging and clinical information will challenge the decision capacity of every oncologist. The understanding of the knowledge management sciences is becoming a priority for radiation oncologists in order for them to tailor their choices to cure and care for individual patients."
DNA sequencing and genetic testing done on cancer cells will become a major factor for choosing between cancer treatment options. Groups of drugs will be delivered to target groups of genetic mutations.
|Share |||Randall Parker, 2013 April 21 09:59 PM|